Research Article
Binary Search Based PSO for Master Node Enumeration and Placement in a Smart Water Metering Network
@INPROCEEDINGS{10.1007/978-3-030-41593-8_8, author={Clement Nyirenda and Samson Nyirongo}, title={Binary Search Based PSO for Master Node Enumeration and Placement in a Smart Water Metering Network}, proceedings={e-Infrastructure and e-Services for Developing Countries. 11th EAI International Conference, AFRICOMM 2019, Porto-Novo, Benin, December 3--4, 2019, Proceedings}, proceedings_a={AFRICOMM}, year={2020}, month={2}, keywords={Smart Water Particle Swarm Optimization Binary Search}, doi={10.1007/978-3-030-41593-8_8} }- Clement Nyirenda
Samson Nyirongo
Year: 2020
Binary Search Based PSO for Master Node Enumeration and Placement in a Smart Water Metering Network
AFRICOMM
Springer
DOI: 10.1007/978-3-030-41593-8_8
Abstract
A Binary Search based Particle Swarm Optimization (BS-PSO) algorithm is proposed for the enumeration and placement of Master Nodes (MNs) in a Smart Water Metering Network (SWMN). The merit of this proposal is that it can simultaneously optimize the number of MNs as well as their locations in the SWMN. The Binary Search (BS) Mechanism searches a pre-specified range of integers for the optimal number of MNs. This algorithm iteratively invokes the PSO algorithm which generates particles based on the chosen number of MNs. The PSO uses these particles to determine MN coordinates in the fitness function evaluation process within the underlying SWMN simulation. The packet delivery ratio (PDR) is designated as the fitness value for the particle. Results for 10 BS-PSO optimization runs show that the median optimal number of MNs is 15 and that the mean PDR of 96% can be realized. As part of future work, more optimization runs will be conducted to enhance the generalization of the results. The extension of this concept to other optimization algorithms such as Differential Evolution will also be considered.